Recommendation system for vehicle passengers

Abstract

A recommendation system for a unique user of a vehicle that predicts one or more recommended commercial establishments includes a centralized computing unit in wireless communication with the vehicle and a plurality of remotely located vehicles. The centralized computing unit score and ranks, based on a personality profile of the unique user of the vehicle, a plurality of potential commercial establishments to determine an initial list of recommended commercial establishments. The personality profile is based on commercial establishments visited by the unique user and a plurality of users, and the plurality of users each represent an individual associated with one of the remotely located vehicles. The centralized computing units re-rank the initial list of recommended commercial establishments based on one or more additional criteria factors to determine a final list of recommended commercial establishments.

What is claimed is: 
     
         1 . A recommendation system for a unique user of a vehicle that predicts one or more recommended commercial establishments, the recommendation system comprising:
 a centralized computing unit in wireless communication with the vehicle and a plurality of remotely located vehicles that executes instructions to:
 score and rank, based on a personality profile of the unique user of the vehicle, a plurality of potential commercial establishments to determine an initial list of recommended commercial establishments, wherein the personality profile is based on commercial establishments visited by the unique user and a plurality of users, and the plurality of users each represent an individual associated with one of the remotely located vehicles; and 
 re-rank the initial list of recommended commercial establishments based on one or more additional criteria factors to determine a final list of recommended commercial establishments, wherein the recommendation system updates the personality profile of the unique user as the vehicle is driven based on one or more commercial establishments that are visited by the unique user. 
   
     
     
         2 . The recommendation system of  claim 1 , wherein the centralized computing unit stores a pool of all commercial establishments presently available. 
     
     
         3 . The recommendation system of  claim 2 , wherein the centralized computing unit executes instructions to:
 receive a query, wherein the query indicates a geographical location of the unique user and a type of commercial establishment; and   in response to receiving the query, filter the pool of all commercial establishments presently available to determine a subset of potential commercial establishments, wherein the plurality of potential commercial establishments are part of the subset of potential commercial establishments.   
     
     
         4 . The recommendation system of  claim 3 , wherein the query is either a specific destination entered by the unique user or a request for all applicable commercial establishments of a particular type within a selected radius. 
     
     
         5 . The recommendation system of  claim 3 , wherein the pool of all commercial establishments are filtered based on the geographical location of the unique user and the type of commercial establishment required. 
     
     
         6 . The recommendation system of  claim 1 , wherein a neural network scores and ranks of the plurality of potential commercial establishments. 
     
     
         7 . The recommendation system of  claim 6 , wherein the neural network includes a query embedding tower and an establishment embedding tower. 
     
     
         8 . The recommendation system of  claim 7 , wherein the query embedding tower includes information from a query entered by the unique user, and the establishment embedding tower includes previously visited commercial establishments. 
     
     
         9 . The recommendation system of  claim 6 , wherein each recommended commercial establishment that is part of the initial list of recommended commercial establishments includes a probability score, wherein a sum of each probability score that is part of the initial list of recommended commercial establishments is equal to 1. 
     
     
         10 . The recommendation system of  claim 1 , wherein the centralized computing unit executes instructions to:
 receive a query requesting a new destination, wherein the vehicle is in route to an original destination; and   in response to receiving the query requesting a new destination, determine a final list of new recommended commercial establishments.   
     
     
         11 . The recommendation system of  claim 1 , wherein the centralized computing unit is in wireless communication with a personal electronic device, wherein a calendar for the unique user is stored in memory of the personal electronic device, and wherein the centralized computing unit executes instructions to:
 predict one or more recommended commercial establishments based on appointments entered in the calendar for the unique user.   
     
     
         12 . The recommendation system of  claim 1 , wherein the one or more additional criteria factors include one or more of the following: travel time, fuel efficiency, weather, time of day, explicit dislikes of the unique user, and diversity of options. 
     
     
         13 . The recommendation system of  claim 1 , wherein the personality profile includes demographic information of the unique user, information related to commercial establishments the unique user has visited, and information related to commercial establishments that the users associated with the remotely located vehicles have visited. 
     
     
         14 . The recommendation system of  claim 13 , wherein the information related to commercial establishments the unique user and the plurality of users have visited include one or more of the following: an amount of time spent at a specific establishment, a type of commercial establishment, a location of the specific establishment, a date the specific establishment was visited, and a frequency that the specific establishment is visited. 
     
     
         15 . The recommendation system of  claim 1 , wherein the centralized computing unit executes instructions to:
 receive demographic information related to the unique user over a wireless network from a controller of the vehicle; and   build an initialized version of the personality profile of the unique user based on the demographic information related to the unique user.   
     
     
         16 . The recommendation system of  claim 15 , wherein the centralized computing unit executes instructions to:
 further build the initialized version of the personality profile based on commercial establishments visited by the plurality of users associated with the remotely located vehicles, wherein the plurality of users have at least one similar demographic category as the unique user.   
     
     
         17 . A method for predicting one or more recommended commercial establishments for a unique user of a vehicle, the method comprising:
 scoring and ranking a plurality of potential commercial establishments based on a personality profile of the unique user to determine an initial list of recommended commercial establishments by a centralized computing unit, wherein the personality profile is based on commercial establishments visited by the unique user and a plurality of users, wherein the plurality of users each represent an individual associated with one of a plurality of remotely located vehicles; and   re-ranking the initial list of recommended commercial establishments based on one or more additional criteria factors to determine a final list of recommended commercial establishments, wherein the personality profile of the unique user is updated as the vehicle is driven based on one or more commercial establishments that are visited by the unique user, and wherein the centralized computing unit stores a pool of all commercial establishments presently available.   
     
     
         18 . The method of  claim 17 , wherein the method further comprises:
 receiving a query, wherein the query indicates a geographical location of the unique user and a type of commercial establishment.   
     
     
         19 . The method of  claim 18 , further comprising:
 in response to receiving the query, filtering a pool of all commercial establishments presently available to determine a subset of potential commercial establishments, wherein the plurality of potential commercial establishments are part of the subset of potential commercial establishments.   
     
     
         20 . The method of  claim 17 , further comprising:
 receiving demographic information related to the unique user over a wireless network from a controller of the vehicle; and   building an initialized version of the personality profile of the unique user based on the demographic information related to the unique user.